š New Book Out Now: Building Modern Data Pipelines with dbt š
Excited to share that our new book āBuilding Modern Data Pipelines with dbt: From Raw Data to Gold Standard with the Medallion Architectureā is officially out now! š
We wrote this book to provide a practical, hands-on guide to one of the most important tools in the modern data stack: dbt.
This book will take you step by step through building data pipelines from scratch with dbt. Youāll follow a hands-on approach, supported by practical examples and clear visualizations that make complex concepts easy to understand.
š§ Learn dbt from Scratch Master the essentials of dbt - from setting up your first dbt project to building efficient data models. Explore advanced features like custom macros, data tests, data contracts, exposures, and managing access with grants.
š» Hands-On Project Work through a complete project using a fictional dataset. Implement each step yourself and gain practical, real-world dbt skills along the way.
š Medallion Architecture Learn how to structure your project with the Medallion Architecture for scalable, high-quality data pipelines. Process your data step by step, from its raw form in the Bronze layer, through the refined Silver layer, into a business-ready format in the Gold layer.
šØāš» Perfect for Professionals and Newcomers This book is suitable for both beginners and experienced professionals in the data world. A basic understanding of data concepts, as well as some initial experience with SQL, is beneficial in certain sections. The book is intended for: - BeginnersĀ who want to explore dbt in greater depth and are looking for a hands-on, practical introduction. - dbt usersĀ who want to extend their knowledge, such as learning how to combine dbt with the medallion architecture or preparing for the dbt Analytics Engineering Exam. - Data professionals, such as data engineers, data scientists, and data analysts, who want to discover the potential of dbt as a core transformation and analytics engineering tool. - StudentsĀ and aspiring data professionals who want to learn how end-to-end data projects can be efficiently implemented in practice using dbt. - Decision-makersĀ who want to develop and implement an effective, scalable data strategy based on modern analytics engineering principles.
š¬ Have a look and let us know what you think ā weād appreciate your feedback!
Large language models (LLMs) have revolutionized artificial intelligence, unlocking new levels of understanding and creativity. But AIās journey is far from overnight ā itās been shaped by decades of innovation, setbacks, and breakthroughs. In this post, weāll explore the pivotal moments in AIās history ā from the early perceptron and initial optimism to AI winters, the deep learning comeback, and the rise of todayās powerful transformers and LLMs.
Exploring this history helps us appreciate how much AI has grown and the challenges and opportunities still ahead.
What Are AI Hallucinations? Causes, Examples, and Why They Matter
AI is incredible. It can help you write emails, explain complex ideas, brainstorm, and even code. But sometimes, it gets things completely wrong ā and says it like itās 100% right. This strange behavior is known as an AI hallucination: when an AI gives an answer that sounds correct but isn't true. In this post, youāll learn what AI hallucinations are, why they happen, and why they matter ā especially if you're using AI for work, learning, or building products.
RAG is an advanced AI architecture that combines the power of retrieval and generation to deliver smarter, more accurate responses. Instead of relying solely on what the model āremembers,ā RAG can pull in external knowledge in real time ā just like how we search the web to answer questions.
š§ How it works:1ļøā£ Retrieval ā RAG first searches a knowledge base (like documents or a database) for relevant context.2ļøā£ Generation ā It then uses a language model to generate a response based on that retrieved context.
š Why context matters:Traditional language models often generate responses based only on training data, which can lead to outdated or incorrect information. RAG injects real-world, current context into the response, improving relevance, accuracy, and trust.
āØ Key Benefits of RAG:ā Context-aware and grounded answersā Less hallucination and misinformationā Dynamic updates without retraining the model
š” RAG is used in chatbots, search engines, customer support, and any app where reliable, knowledge-rich responses matter.
š Want to dive deeper?Check out the detailed tutorial by Deep Learning Nerds Academy to learn how RAG works under the hood and how to build it step-by-step:š deeplearningnerds.com/retrieval-augmented-generation-rag-the-key-to-smarter-ai-responses
Deep Learning Nerds
š New Book Out Now: Building Modern Data Pipelines with dbt š
Excited to share that our new book āBuilding Modern Data Pipelines with dbt: From Raw Data to Gold Standard with the Medallion Architectureā is officially out now! š
We wrote this book to provide a practical, hands-on guide to one of the most important tools in the modern data stack: dbt.
Find the book on Amazon š mybook.to/2UP6
This book will take you step by step through building data pipelines from scratch with dbt. Youāll follow a hands-on approach, supported by practical examples and clear visualizations that make complex concepts easy to understand.
š§ Learn dbt from Scratch
Master the essentials of dbt - from setting up your first dbt project to building efficient data models. Explore advanced features like custom macros, data tests, data contracts, exposures, and managing access with grants.
š» Hands-On Project
Work through a complete project using a fictional dataset. Implement each step yourself and gain practical, real-world dbt skills along the way.
š Medallion Architecture
Learn how to structure your project with the Medallion Architecture for scalable, high-quality data pipelines. Process your data step by step, from its raw form in the Bronze layer, through the refined Silver layer, into a business-ready format in the Gold layer.
šØāš» Perfect for Professionals and Newcomers
This book is suitable for both beginners and experienced professionals in the data world. A basic understanding of data concepts, as well as some initial experience with SQL, is beneficial in certain sections. The book is intended for:
- BeginnersĀ who want to explore dbt in greater depth and are looking for a hands-on, practical introduction.
- dbt usersĀ who want to extend their knowledge, such as learning how to combine dbt with the medallion architecture or preparing for the dbt Analytics Engineering Exam.
- Data professionals, such as data engineers, data scientists, and data analysts, who want to discover the potential of dbt as a core transformation and analytics engineering tool.
- StudentsĀ and aspiring data professionals who want to learn how end-to-end data projects can be efficiently implemented in practice using dbt.
- Decision-makersĀ who want to develop and implement an effective, scalable data strategy based on modern analytics engineering principles.
š¬ Have a look and let us know what you think ā weād appreciate your feedback!
#dbt #dbtlabs #deeplearningnerds #dataengineer #medallionarchitecture #dataanalytics
3 months ago | [YT] | 1
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Deep Learning Nerds
The Evolution of AI: From Primitive Neural Networks to Cutting-Edge Large Language Models (LLMs)
www.deeplearningnerds.com/the-evolution-of-ai-fromā¦
Large language models (LLMs) have revolutionized artificial intelligence, unlocking new levels of understanding and creativity. But AIās journey is far from overnight ā itās been shaped by decades of innovation, setbacks, and breakthroughs. In this post, weāll explore the pivotal moments in AIās history ā from the early perceptron and initial optimism to AI winters, the deep learning comeback, and the rise of todayās powerful transformers and LLMs.
Exploring this history helps us appreciate how much AI has grown and the challenges and opportunities still ahead.
#llm #ai #genai #deeplearning #artificialintelligence
11 months ago | [YT] | 0
View 0 replies
Deep Learning Nerds
What Are AI Hallucinations? Causes, Examples, and Why They Matter
AI is incredible. It can help you write emails, explain complex ideas, brainstorm, and even code. But sometimes, it gets things completely wrong ā and says it like itās 100% right. This strange behavior is known as an AI hallucination: when an AI gives an answer that sounds correct but isn't true. In this post, youāll learn what AI hallucinations are, why they happen, and why they matter ā especially if you're using AI for work, learning, or building products.
www.deeplearningnerds.com/what-are-ai-hallucinatioā¦
#ai #genai #llm #rag #deeplearning
11 months ago | [YT] | 0
View 0 replies
Deep Learning Nerds
RAG is an advanced AI architecture that combines the power of retrieval and generation to deliver smarter, more accurate responses. Instead of relying solely on what the model āremembers,ā RAG can pull in external knowledge in real time ā just like how we search the web to answer questions.
š§ How it works:1ļøā£ Retrieval ā RAG first searches a knowledge base (like documents or a database) for relevant context.2ļøā£ Generation ā It then uses a language model to generate a response based on that retrieved context.
š Why context matters:Traditional language models often generate responses based only on training data, which can lead to outdated or incorrect information. RAG injects real-world, current context into the response, improving relevance, accuracy, and trust.
āØ Key Benefits of RAG:ā Context-aware and grounded answersā Less hallucination and misinformationā Dynamic updates without retraining the model
š” RAG is used in chatbots, search engines, customer support, and any app where reliable, knowledge-rich responses matter.
š Want to dive deeper?Check out the detailed tutorial by Deep Learning Nerds Academy to learn how RAG works under the hood and how to build it step-by-step:š deeplearningnerds.com/retrieval-augmented-generation-rag-the-key-to-smarter-ai-responses
www.instagram.com/p/DLIWBybsMfm/
#rag #ai #genai #chatgpt #llm
11 months ago | [YT] | 0
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Deep Learning Nerds
NEW VIDEO ONLINE!
What are GANs?
2 years ago | [YT] | 0
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Deep Learning Nerds
NEW FABRIC VIDEO ONLINE!
We explain how to create a Data Pipeline in Microsoft Fabric.
2 years ago | [YT] | 0
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Deep Learning Nerds
NEW FABRIC VIDEO ONLINE!
We explain how to create a Workspace in Microsoft Fabric.
2 years ago | [YT] | 0
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